Biofuels are presented in rich countries as a solution to two crises: the climate crisis and the oil crisis. But they may not be a solution to either, and instead are contributing to a third: the current food crisis.
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In response to energy security concerns, alternative energy programs such as biomass energy systems are being
developed to provide energy in the 21st century. For the biomass industry to expand, a variety of feedstocks will need
to be utilized. Large scale production of bioenergy crops could have significant impacts on the United States agricultural
sector in terms of quantities, prices and production location of traditional crops as well as farm income. Though
Crop intensification is often thought to increase greenhouse gas (GHG) emissions, but studies in which crop management is optimized to exploit crop yield potential are rare. We conducted a field study in eastern Nebraska, USA to quantify GHG emissions, changes in soil organic carbon (SOC) and the net global warming potential (GWP) in four irrigated systems: continuous maize with recommended best management practices (CC-rec) or intensive management (CC-int) and maize–soybean rotation with recommended (CS-rec) or intensive management (CS-int).
Switchgrass (Panicum virgatum L.) is a perennial grass native to the United States that has been studied as a sustainable source of biomass fuel. Although many field-scale studies have examined the potential of this grass as a bioenergy crop, these studies have not been integrated. In this study, we present an empirical model for switchgrass yield and use this model to predict yield for the conterminous United States. We added environmental covariates to assembled yield data from field trials based on geographic location. We developed empirical models based on these data.
USDA Agricultural Projections for 2011-20, released in February 2011, provide longrun projections for the farm sector for the next 10 years. These annual projections cover agricultural commodities, agricultural trade, and aggregate indicators of the sector, such as farm income and food prices.
Important assumptions for the projections include:
PEATSim (Partial Equilibrium Agricultural Trade Simulation) is a dynamic, partial equilibrium, mathematical-based model that enables users to reach analytical solutions to problems, given a set of parameters, data, and initial
conditions. This theoretical tool developed by ERS incorporates a wide range of domestic and border policies that enables it to estimate the market and trade effects of policy changes on agricultural markets. PEATSim captures
Agricultural markets often feature significant transport costs and spatially distributed production and processing which causes spatial imperfect competition. Spatial economics considers the firms’ decisions regarding location and spatial price strategy separately, usually on the demand side, and under restrictive assumptions. Therefore, alternative approaches are needed to explain, e.g., the location of new ethanol plants in the U.S. at peripheral as well as at central locations and the observation of different spatial price strategies in the market.
When the lignocellulosic biofuels industry reaches maturity and many types of biomass sources become economically viable, management of multiple feedstock supplies – that vary in their yields, density (tons per unit area), harvest window, storage and seasonal costs, storage losses, transport distance to the production plant – will become increasingly important for the success of individual enterprises. The manager’s feedstock procurement problem is modeled as a multi-period sequence problem to account for dynamic management over time.
This database contains current and historical official USDA data on production, supply and distribution of agricultural commodities for the United States and key producing and consuming countries.
The purpose of this study is to analyse the economical and environmental performance of switchgrass and miscanthus production and supply chains in the European Union (EU25), for the years 2004 and 2030. The environmental performance refers to the greenhouse gas (GHG) emissions, the primary fossil energy use and to the impact on fresh water reserves, soil erosion and biodiversity. Analyses are carried out for regions in five countries.